Gemma on NVIDIA Ada

Can I run Gemma 3 4B on an RTX 4070 Ti Super?

Yes. Gemma 3 4B at Q4_K_M uses 3.6 GB of the 14.2 GB available on a RTX 4070 Ti Super, and runs at about 146 tokens per second. You can push the context to 128K.

Runs comfortably

3.6 GB of 14.2 GB · 25%
014 GB
Weights 2.5 GB
KV cache 0.3 GB
Runtime overhead 0.8 GB

Gemma 3 4B at Q4_K_M leaves 10.7 GB spare on a RTX 4070 Ti Super. There is room to raise the context length or move up a quantisation level.

Generation146tok/s
Prompt processing4298tok/s
Max context128Ktokens
KV per 1K tokens0GB

Every quantisation of Gemma 3 4B on a RTX 4070 Ti Super

Highlighted row is the highest quality that still fits at 8K context.

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 8.0 GB 9.1 GB Runs comfortably 128K 48.6
INT8 / W8A8 8.50 4.1 GB 5.2 GB Runs comfortably 128K 91.8
Q8_0 (GGUF) 8.50 4.1 GB 5.2 GB Runs comfortably 128K 91.8
FP8 (E4M3) 8.00 4.0 GB 5.1 GB Runs comfortably 128K 93.9
Q6_K 6.56 3.3 GB 4.4 GB Runs comfortably 128K 113
AWQ 4-bit 4.25 3.0 GB 4.1 GB Runs comfortably 128K 121
GPTQ 4-bit 4.25 3.0 GB 4.1 GB Runs comfortably 128K 121
MXFP4 4.25 3.0 GB 4.1 GB Runs comfortably 128K 121
Q5_K_M 5.67 2.8 GB 3.9 GB Runs comfortably 128K 129
Q5_K_S 5.52 2.8 GB 3.9 GB Runs comfortably 128K 132
Q4_K_M 4.85 2.5 GB 3.6 GB Runs comfortably 128K 146
Q4_K_S 4.58 2.4 GB 3.5 GB Runs comfortably 128K 152
Q4_0 4.55 2.4 GB 3.4 GB Runs comfortably 128K 153
IQ4_XS 4.25 2.2 GB 3.3 GB Runs comfortably 128K 161
Q3_K_M 3.91 2.1 GB 3.2 GB Runs comfortably 128K 170
IQ3_M 3.70 2.0 GB 3.1 GB Runs comfortably 128K 177
IQ3_XXS 3.06 1.7 GB 2.8 GB Runs comfortably 128K 201
Q2_K 2.63 1.5 GB 2.6 GB Runs comfortably 128K 221
IQ2_XXS 2.06 1.3 GB 2.4 GB Runs comfortably 128K 254
IQ1_M 1.75 1.2 GB 2.3 GB Runs comfortably 128K 277

Also worth checking

Gemma 3 4B on every GPU
Full hardware tableEverything that runs on a RTX 4070 Ti Super
Full model tableWhy the KV cache is the part that bites
Guide